{"title":"Focusing Viral Risk Ranking Tool on Prediction","authors":"Katherine Budeski, Marc Lipsitch","doi":"arxiv-2409.04932","DOIUrl":null,"url":null,"abstract":"Preparing to rapidly respond to emerging infectious diseases is becoming ever\nmore critical. \"SpillOver: Viral Risk Ranking\" is an open-source tool developed\nto evaluate novel wildlife-origin viruses for their risk of spillover from\nanimals to humans and their risk of spreading in human populations. However,\nseveral of the factors used in the risk assessment are dependent on evidence of\nprevious zoonotic spillover and/or sustained transmission in humans. Therefore,\nwe performed a reanalysis of the \"Ranking Comparison\" after removing eight\nfactors that require post-spillover knowledge and compared the adjusted risk\nrankings to the originals. The top 10 viruses as ranked by their adjusted\nscores also had very high original scores. However, the predictive power of the\ntool for whether a virus was a human virus or not as classified in the\nSpillover database deteriorated when these eight factors were removed. The area\nunder the receiver operating characteristic curves (AUROC) for the original\nscore, 0.94, decreased to 0.73 for the adjusted scores. Furthermore, we\ncompared the mean and standard deviation of the human and non-human viruses at\nthe factor level. Most of the excluded spillover-dependent factors had\ndissimilar means between the human and non-human virus groups compared to the\nnon-spillover dependent factors, which frequently demonstrated similar means\nbetween the two groups with some exceptions. We concluded that the original\nformulation of the tool depended heavily on spillover-dependent factors to\n\"predict\" the risk of zoonotic spillover for a novel virus. Future iterations\nof the tool should take into consideration other non-spillover dependent\nfactors and omit those that are spillover-dependent to ensure the tool is fit\nfor purpose.","PeriodicalId":501266,"journal":{"name":"arXiv - QuanBio - Quantitative Methods","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Quantitative Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Preparing to rapidly respond to emerging infectious diseases is becoming ever
more critical. "SpillOver: Viral Risk Ranking" is an open-source tool developed
to evaluate novel wildlife-origin viruses for their risk of spillover from
animals to humans and their risk of spreading in human populations. However,
several of the factors used in the risk assessment are dependent on evidence of
previous zoonotic spillover and/or sustained transmission in humans. Therefore,
we performed a reanalysis of the "Ranking Comparison" after removing eight
factors that require post-spillover knowledge and compared the adjusted risk
rankings to the originals. The top 10 viruses as ranked by their adjusted
scores also had very high original scores. However, the predictive power of the
tool for whether a virus was a human virus or not as classified in the
Spillover database deteriorated when these eight factors were removed. The area
under the receiver operating characteristic curves (AUROC) for the original
score, 0.94, decreased to 0.73 for the adjusted scores. Furthermore, we
compared the mean and standard deviation of the human and non-human viruses at
the factor level. Most of the excluded spillover-dependent factors had
dissimilar means between the human and non-human virus groups compared to the
non-spillover dependent factors, which frequently demonstrated similar means
between the two groups with some exceptions. We concluded that the original
formulation of the tool depended heavily on spillover-dependent factors to
"predict" the risk of zoonotic spillover for a novel virus. Future iterations
of the tool should take into consideration other non-spillover dependent
factors and omit those that are spillover-dependent to ensure the tool is fit
for purpose.